Elaborate on the Business Understanding: determine business

Elaborate on the Business Understanding: determine business objectives and possible ways to achieve them. Assess the situation, making assumptions where necessary, and determine data mining goals
“Zorg en Zekerheid is a medium-sized and independent regional health insurer in theNetherlands, with more than 460 employees and more than 380,000 policyholders. Thecompany is committed to providing accessible and affordable healthcare. The majority ofpolicyholders and healthcare providers submit claims for treatments that have actuallytaken place. However, a small number commit fraud — for example by adapting invoices.There are instances of policyholders who, after returning from vacation, submit invoicesfor medical costs made abroad. Further examination shows that the invoiced amount hasbeen altered and is many times higher than the original amount. There are also instancesof “up-coding” — a form of fraud committed by healthcare providers performing simpleservices but claiming for more complex alternatives, which results in higher costs.”Zorg en Zekerheid needed a more accurate and efficient solution to detect claims fraud.Assume you have been hired by Zorg en Zekerheid to work on this project — to build apredictive modelling solution that translates many data elements from a diverse range ofsources into quantitative risk ratings for fraudulent claims.TasksHaving covered the CRISP-DM methodology at length at the university, you decide toapply it to this project.You are free to make reasonable assumptions about possible data sources. However, keepin mind that some data may not be allowed to be used in the Netherlands. You need notknow the precise laws in the Netherlands or elsewhere, just highlight your legal/ethicalconcerns if any arise.(a) Elaborate on the Business Understanding: determine business objectives andpossible ways to achieve them. Assess the situation, making assumptions wherenecessary, and determine data mining goals. [35%](b) Discuss the next stages of Data Understanding and Data Preparation. How does yourplan of these stages look like? Think of additional data sources that might be usefulfor this problem. Be creative but realistic. Describe all data sources in terms of theirexpected properties (structured, unstructured, 4Vs). Comment on practicalchallenges that may arise from using these sources. [30%](c) What variable do you expect to use as target? What specific challenges yourpredictive analytics on detecting fraudulent claims might face using the past data?Why will you need to partition the data for predictive modelling? Will over-samplingbe needed? [35%]

 
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